Citation: |
[1] |
A. Blake, Boundary conditions of lightness computation in mondrian world, Computer Vision Graphics and Image Processing, 32 (1985), 314-327.doi: 10.1016/0734-189X(85)90054-4. |
[2] |
D. Brainard and B. Wandell, Analysis of the Retinex theory of color vision, J. Opt. Soc. of Am. A, 3 (1986), 1651-1661.doi: 10.1364/JOSAA.3.001651. |
[3] |
L. Bregman, A relaxation method of finding the common points of convex sets and its application to the solution of problems in convex programming, USSR Comput Math and Math. Phys., 7 (1967), 200-217. |
[4] |
A. Buades, B. Coll and J. M. Morel, A review of image denoising algorithms, with a new one, Multiscale Model. Simul., 4 (2005), 490-530. |
[5] |
J. Frankle and J. McCann, Method and apparatus for lightness imaging, US Patent no. 4384336, (1983). |
[6] |
B. Funt, F. Ciuera and J. McCann, Retinex in Matlab, Journal of Electronic Imaging, 13 (2004), 48-57.doi: 10.1117/1.1636761. |
[7] |
G. Gilboa and S. Osher, Nonlocal operators with applications to image processing, Multiscale Model. Simul., 7 (2008), 1005-1028. |
[8] |
T. Goldstein and S. Osher, The split Bregman algorithm for L1 regularized problems, SIAM J. Imaging Sci., 2 (2009), 323-343. |
[9] |
T. Goldstein, X. Bresson and S. Osher, Geometric applications of the split Bregman method: Segmentation and surface reconstruction, J. Sci. Comput., 45 (2010), 272-293.doi: 10.1007/s10915-009-9331-z. |
[10] |
B. K. P. Horn, Determining lightness from an image, Computer Graphics and Image Processing, 3 (1974), 277-299. |
[11] |
D. J. Jobson, Z. Rahman and G. A. Woodell, A multiscale retinex for bridging the gap between color images and the human observation of scenes, IEEE Trans. on Image Processing, 6 (1997), 965-976. |
[12] |
R. Kimmel, M. Elad, D. Shaked, R. Keshet and I. Sobel, A variational framework for retinex, Int. Journal of Computer Vision, 52 (2003), 7-23.doi: 10.1023/A:1022314423998. |
[13] |
E. H. Land and J. J. McCann, Lightness and the retinex theory, J. Opt. Soc. Am., 61 (1971), 1-11.doi: 10.1364/JOSA.61.000001. |
[14] |
E. H. Land, The retinex theory of color vision, Sci. Amer., 237 (1977), 108-128.doi: 10.1038/scientificamerican1277-108. |
[15] |
E. H. Land, Recent advances in the Retinex theory and some implications for cortical computations: Color vision and the natural image, Proc. Nat. Acad. Sci. USA, 80 (1983), 5163-5169.doi: 10.1073/pnas.80.16.5163. |
[16] |
E. H. Land, An alternative technique for computation of the designator in the Retinex of color vision, Proc. Nat. Acad. Sci. USA, 83 (1986), 3078-3080.doi: 10.1073/pnas.83.10.3078. |
[17] |
Y. Lei, Y. Zhou and J. Li, An investigation of retinex algorithms for image enhancement, Jouranl of Electron, China, 24 (2007), 696-700. |
[18] |
W. Ma, J. M. Morel, A. Chien and S. Osher, An L1-based variational model for Retinex theory and its application to medical images, IEEE Conference on Computer Vision and Pattern Recognition, (2011), 153-160. |
[19] |
J. M. Morel, A. B. Petro and C. Sbert, Fast implementation of color constancy algorithms, Proc. SPIE, 7241 (2009). |
[20] |
J. M. Morel, A. B. Petro and C. Sbert, A PDE formalization of the retinex theory, IEEE Transaction on Image Processing, 19 (2010), 2825-2837. |
[21] |
S. Osher, M. Burger, D. Goldfarb, J. Xu and W. Yin, An iterative regularization method for total variation based image restoration, SIAM Multiscale Model. and Simu., 4 (2005), 460-489. |
[22] |
E. Provenzi, M. Fierro, A. Rizzi, L. De Carli, D. Gadia and D. Marini, Random spray retinex: A new retinex implementation to investigate the local properties of the model, IEEE Transactions on Image Processing, 16 (2007), 162-171.doi: 10.1109/TIP.2006.884946. |
[23] |
L. I. Rudin, S. Osher and E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica, D(60) (1992), 259-268. |
[24] |
X. Zhang, M. Burger, X. Bresson and S. Osher, Bregmanized nonlocal regularization for deconvolution and sparse reconstruction, SIAM J. Imaging Sci., 3 (2010), 253-276. |